An Efficient COVID-19 Prediction Model Validated with the Cases of China, Italy and Spain: Total or Partial Lockdowns?
Identifieur interne : 001725 ( Main/Exploration ); précédent : 001724; suivant : 001726An Efficient COVID-19 Prediction Model Validated with the Cases of China, Italy and Spain: Total or Partial Lockdowns?
Auteurs : Samuel Sanchez-Caballero [Espagne] ; Miguel A. Selles [Espagne] ; Miguel A. Peydro [Espagne] ; Elena Perez-Bernabeu [Espagne]Source :
- Journal of clinical medicine [ 2077-0383 ] ; 2020.
Abstract
The present work develops an accurate prediction model of the COVID-19 pandemic, capable not only of fitting data with a high regression coefficient but also to predict the overall infections and the infection peak day as well. The model is based on the Verhulst equation, which has been used to fit the data of the COVID-19 spread in China, Italy, and Spain. This model has been used to predict both the infection peak day, and the total infected people in Italy and Spain. With this prediction model, the overall infections, the infection peak, and date can accurately be predicted one week before they occur. According to the study, the infection peak took place on 23 March in Italy, and on 29 March in Spain. Moreover, the influence of the total and partial lockdowns has been studied, without finding any meaningful difference in the disease spread. However, the infected population, and the rate of new infections at the start of the lockdown, seem to play an important role in the infection spread. The developed model is not only an important tool to predict the disease spread, but also gives some significant clues about the main factors that affect to the COVID-19 spread, and quantifies the effects of partial and total lockdowns as well.
DOI: 10.3390/jcm9051547
PubMed: 32443871
PubMed Central: PMC7290738
Affiliations:
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Selles</name><affiliation wicri:level="2"><nlm:affiliation>Technological Institute of Materials, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.</nlm:affiliation><country xml:lang="fr">Espagne</country><wicri:regionArea>Technological Institute of Materials, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy</wicri:regionArea><placeName><region nuts="2" type="communauté">Communauté valencienne</region></placeName></affiliation></author><author><name sortKey="Peydro, Miguel A" sort="Peydro, Miguel A" uniqKey="Peydro M" first="Miguel A" last="Peydro">Miguel A. Peydro</name><affiliation wicri:level="2"><nlm:affiliation>Technological Institute of Materials, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.</nlm:affiliation><country xml:lang="fr">Espagne</country><wicri:regionArea>Technological Institute of Materials, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy</wicri:regionArea><placeName><region nuts="2" type="communauté">Communauté valencienne</region></placeName></affiliation></author><author><name sortKey="Perez Bernabeu, Elena" sort="Perez Bernabeu, Elena" uniqKey="Perez Bernabeu E" first="Elena" last="Perez-Bernabeu">Elena Perez-Bernabeu</name><affiliation wicri:level="2"><nlm:affiliation>Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.</nlm:affiliation><country xml:lang="fr">Espagne</country><wicri:regionArea>Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy</wicri:regionArea><placeName><region nuts="2" type="communauté">Communauté valencienne</region></placeName></affiliation></author></analytic><series><title level="j">Journal of clinical medicine</title><idno type="ISSN">2077-0383</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The present work develops an accurate prediction model of the COVID-19 pandemic, capable not only of fitting data with a high regression coefficient but also to predict the overall infections and the infection peak day as well. The model is based on the Verhulst equation, which has been used to fit the data of the COVID-19 spread in China, Italy, and Spain. This model has been used to predict both the infection peak day, and the total infected people in Italy and Spain. With this prediction model, the overall infections, the infection peak, and date can accurately be predicted one week before they occur. According to the study, the infection peak took place on 23 March in Italy, and on 29 March in Spain. Moreover, the influence of the total and partial lockdowns has been studied, without finding any meaningful difference in the disease spread. However, the infected population, and the rate of new infections at the start of the lockdown, seem to play an important role in the infection spread. The developed model is not only an important tool to predict the disease spread, but also gives some significant clues about the main factors that affect to the COVID-19 spread, and quantifies the effects of partial and total lockdowns as well.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">32443871</PMID><DateRevised><Year>2020</Year><Month>06</Month><Day>19</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Print">2077-0383</ISSN><JournalIssue CitedMedium="Print"><Volume>9</Volume><Issue>5</Issue><PubDate><Year>2020</Year><Month>May</Month><Day>20</Day></PubDate></JournalIssue><Title>Journal of clinical medicine</Title><ISOAbbreviation>J Clin Med</ISOAbbreviation></Journal><ArticleTitle>An Efficient COVID-19 Prediction Model Validated with the Cases of China, Italy and Spain: Total or Partial Lockdowns?</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">E1547</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.3390/jcm9051547</ELocationID><Abstract><AbstractText>The present work develops an accurate prediction model of the COVID-19 pandemic, capable not only of fitting data with a high regression coefficient but also to predict the overall infections and the infection peak day as well. The model is based on the Verhulst equation, which has been used to fit the data of the COVID-19 spread in China, Italy, and Spain. This model has been used to predict both the infection peak day, and the total infected people in Italy and Spain. With this prediction model, the overall infections, the infection peak, and date can accurately be predicted one week before they occur. According to the study, the infection peak took place on 23 March in Italy, and on 29 March in Spain. Moreover, the influence of the total and partial lockdowns has been studied, without finding any meaningful difference in the disease spread. However, the infected population, and the rate of new infections at the start of the lockdown, seem to play an important role in the infection spread. The developed model is not only an important tool to predict the disease spread, but also gives some significant clues about the main factors that affect to the COVID-19 spread, and quantifies the effects of partial and total lockdowns as well.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Sanchez-Caballero</LastName><ForeName>Samuel</ForeName><Initials>S</Initials><Identifier Source="ORCID">0000-0001-5322-8082</Identifier><AffiliationInfo><Affiliation>Institute of Manufacturing and Design, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Selles</LastName><ForeName>Miguel A</ForeName><Initials>MA</Initials><Identifier Source="ORCID">0000-0002-0784-5757</Identifier><AffiliationInfo><Affiliation>Technological Institute of Materials, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Peydro</LastName><ForeName>Miguel A</ForeName><Initials>MA</Initials><Identifier Source="ORCID">0000-0002-8503-1505</Identifier><AffiliationInfo><Affiliation>Technological Institute of Materials, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Perez-Bernabeu</LastName><ForeName>Elena</ForeName><Initials>E</Initials><Identifier Source="ORCID">0000-0002-9221-7623</Identifier><AffiliationInfo><Affiliation>Department of Applied Statistics, Operations Research and Quality, Universitat Politècnica de València, Plaza Ferrandiz i Carbonell, 2, 03801 Alcoy, Spain.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate 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sortKey="Peydro, Miguel A" sort="Peydro, Miguel A" uniqKey="Peydro M" first="Miguel A" last="Peydro">Miguel A. Peydro</name><name sortKey="Selles, Miguel A" sort="Selles, Miguel A" uniqKey="Selles M" first="Miguel A" last="Selles">Miguel A. Selles</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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